Method For Inserting and Extracting Multi-Bit Fingerprint Based on Wavelet

ABSTRACT

A method for inserting and extracting a fingerprint based on a wavelet is disclosed. The method includes: a) decomposing an original image into a first sub-band image having low frequency band columns and rows, a second sub-band image having high frequency band columns and low frequency band rows, a third sub-band image having low frequency band columns and high frequency band rows and a fourth sub-band image having high frequency band columns and rows by performing an n-level discrete wavelet transformation on an original image; b) obtaining a human visual system model from the first sub-band image; c) generating an N×N fingerprint basic block by performing a message modulation on a multi-bit fingerprint signal with a security key and adding a synch pattern to the modulated signal; d) repeatedly inserting the fingerprint basic block in to the second, the third and the fourth sub-band images with reference to the human visual system model; and e) generating a fingerprint inserted image by performing an inverse discrete wavelet transformation on the first sub-band image and the fingerprint basic block inserted second, third and fourth sub-band images.

TECHNICAL FIELD

The present invention relates to a method for inserting and extracting amulti-bit fingerprint based on a wavelet transformation, and moreparticularly to a method for extracting a multi-bit fingerprint afterrecovering an image having a geometrical transformation such as arotation, scaling or translation by generating a square fingerprintblock through reconfiguring a multi-bit fingerprint signal with asynchronization signal and repeatedly inserting the square fingerprintblock into wavelet-transformed areas with using the synchronizationsignal.

BACKGROUND ART

As a method of protecting a copyright of multimedia contents in theInternet environment, a watermarking or a fingerprinting scheme wereintroduced. These schemes prove the ownership of the contents byinserting a predetermined signal into the content itself. Thewatermarking scheme inserts owner's information into the contents, andthe fingerprint scheme inserts purchaser's information into the contentswhen the purchaser buys the contents. Using the fingerprint, a purchaserwho illegally distributes the contents can be traced.

It is very important to design a fingerprint to resist illegal attack toeliminate the fingerprint from the contents as well as invisiblyinserting the fingerprint into the contents. The illegal attack may beclassified into a non-geometrical transformation such as compression orfiltering and a geometrical transformation such as rotation, scaling andtranslation.

A conventional fingerprinting scheme based on repeatedly inserting afingerprint is known as an effective method to protect the copyrightfrom the geometrical transformation. According to the conventionalfingerprinting scheme, it is possible to predict a geometrical formationof an image and to recover an original image based on the predictedgeometrical formation by obtaining a periodic auto-correlation patternwhen a fingerprint is extracted. However, such an auto-correlation peakcan be eliminated by the illegal attacks such as the geometrictransformation or the image processing. Therefore, there is greaterdemand to precisely predict a level of geometrical transformation basedon extracted peak candidates.

Disclosure of Invention Technical Problem

An object of the present invention is to provide a method for extractinga multi-bit fingerprint after recovering an image having a geometricaltransformation such as a rotation, scaling or translation by generatinga square fingerprint block through re-configuring a multi-bitfingerprint signal with a synchronization signal and repeatedlyinserting the square fingerprint block into wavelet-transformed areaswith using the synchronization signal in order to effectively protect acopyright of contents from a geometrical attack.

Technical Solution

To achieve these and other advantages and in accordance with the purposeof the present invention, as embodied and broadly described, there isprovided a method of inserting a multi-bit fingerprint based on awavelet including the steps of: a) decomposing an original image into afirst sub-band image having low frequency band columns and rows, asecond sub-band image having high frequency band columns and lowfrequency band rows, a third sub-band image having low frequency bandcolumns and high frequency band rows and a fourth sub-band image havinghigh frequency band columns and rows by performing an n-level discretewavelet transformation on an original image; b) obtaining a human visualsystem model from the first sub-band image; c) generating an N×Nfingerprint basic block by performing a message modulation on amulti-bit fingerprint signal with a security key and adding a synchpattern to the modulated signal; d) repeatedly inserting the fingerprintbasic block in to the second, the third and the fourth sub-band imageswith reference to the human visual system model; and e) generating afingerprint inserted image by performing an inverse discrete wavelettransformation on the first sub-band image and the fingerprint basicblock inserted second, third and fourth sub-band images.

In accordance with another aspect of the present invention, there isprovided a method of extracting a multi-bit fingerprint based on awavelet including the steps of: a) estimating original signal having afingerprint from a fingerprint inserted image; b) detecting a peak froma self-reference pattern obtained from an auto-correlation of theestimated original signal; c) extracting rotation and scalinginformation from the detected peak and correcting a rotationtransformation and a scaling transformation of the original signalhaving the fingerprint based on the extracted rotation and scalinginformation; d) obtaining an estimated fingerprint part signal from thecorrected original signal, extracting translation information from across correlation peak between the estimated fingerprint part signal anda synchronization signal, and correcting a translation transformation ofthe original signal having the fingerprint; and e) extracting afingerprint from the rotation, scaling and translation correctedoriginal signal using a sub-band merge signal.

Advantageous Effects

A method of inserting and extracting a multi-bit fingerprint accordingto the present invention decomposes an original image into sub-bandimages through a wavelet transformation, repeatedly inserts thefingerprint the decomposed sub-band images, and corrects rotation,scaling and translation formations. Therefore, the method of insertingand extracting a multi-bit fingerprint according to the presentinvention can be used to firmly protect multimedia contents from both ofthe geometrical attacks and the lossey compression such as JPEG.Furthermore, the method of inserting and extracting a multi-bitfingerprint according to the present invention also can be used tofirmly protect an image having different messages inserted form acollusion attack such as an averaging attack or a mosaic attack.

BRIEF DESCRIPTION OF THE DRAWINGS

The above objects, other features and advantages of the presentinvention will become more apparent by describing the preferredembodiments thereof with reference to the accompanying drawings, inwhich:

FIG. 1 is a view for showing a method of inserting a multi-bitfingerprint according to an embodiment of the present invention;

FIG. 2 schematically shows a method of extracting a multi-bitfingerprint according to an embodiment of the present invention;

FIG. 3 shows a generation of a multi-bit fingerprint signal in themethod of inserting the multi-bit fingerprint shown in FIG. 1;

FIG. 4 shows a generation of a fingerprint block in the method ofinserting a multi-bit fingerprint in the method of inserting themulti-bit fingerprint shown in FIG. 1;

FIG. 5 shows an insertion of a fingerprint block into wavelet sub-bandareas of the original image in the method of inserting the multi-bitfingerprint shown in FIG. 1;

FIG. 6 shows a generation of a synch part signal used for correcting atranslation of an original image in the method of extracting themulti-bit fingerprint shown in FIG. 2;

FIG. 7 shows a generation of an estimated fingerprint part signal usedto correct the translation of the image in the method of extracting themulti-bit fingerprint shown in FIG. 2; and

FIG. 8 shows a correction of translation transformation and anextraction of the fingerprint information in a method of extracting amulti-bit fingerprint in the method of extracting the multi-bitfingerprint shown in FIG. 2.

BEST MODE FOR CARRYING OUT THE INVENTION

Reference will now be made in detail to the preferred embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings.

FIG. 1 is a view for showing a method of inserting a multi-bitfingerprint according to an embodiment of the present invention.

The method of inserting a multi-bit fingerprint according to the presentembodiment uses a wavelet transformation and an inverse wavelettransformation. The wavelet transformation may be called as a waveletdecomposition. The wavelet transformation is a method of coding an imagethrough dividing the image by a frequency bandwidth of the image using alow-pass filter and a high-pass filter. The wavelet transformation isgenerally used to process images for compressing. In the presentinvention, an original image is divided into a plurality of sub-bandimages by performing a discreet wavelet transformation (DWT) on theoriginal image and a multi-bit fingerprint created according to thepresent invention is inserted into the divided sub-band images. Afterinserting the multi-bit fingerprint, an inverse DWT is performed on thedivided sub-band images to generate a fingerprint inserted image.

While performing the DWT on the original image, the original image isdecomposed using a low-pass filter for columns of the original image anda high-pass filter for rows of the original image because the image isgenerally two-dimensional signal. As a result, the original image isdecomposed into four sub-band images LL₁, LH₁, HL₁ and HH_(1.) Thesub-band image LL₁ is composed of low frequency band columns and rows,the sub-band image LH₁ is composed of low frequency band columns andhigh frequency band rows, the sub-band image HL₁ is composed of highfrequency band columns and low frequency band rows, and the sub-bandimage HH₁ is composed of high frequency band columns and rows. Since thesub-band image LL1 has almost all of information about the originalimage, the sub-band image LL1 is treated as a new image and the DWT maybe performed on the sub-band image LL1 again. Herein, an n-leveldiscrete wavelet transformation denotes that the DWT is performed on animage n times based on the above described method.

Hereinafter, a method of inserting a multi-bit fingerprint according tothe present invention will be described with reference to FIGS. 1 and 3through 5.

At first, sub-band images LL_(n) are obtained by performing an n-levelDWT on an original image. Then, a human visual system (HVS) model isobtained from the sub-band images LL_(n) at step S11. After obtainingthe HVS model, an N×N fingerprint basic block is obtained at step S12 bymodulating a multi-bit fingerprint signal with a security key andinserting a sync pattern into the modulated signal, where the syncpattern is a synchronization signal.

Meanwhile, the n-level DWT is performed on the original image at stepS14 to obtain sub-band images shown in FIG. 1. the N×N fingerprint basicblock generated at the step S12 is repeatedly inserted into the sub-bandimages HL_(n), LH_(n) and HH_(n) at the step S13 with reference to theHVS model obtained in the step S11. Then, the fingerprint inserted imageis obtained by performing the inverse DWT on the sub-band image LL_(n)and the N×N fingerprint basic block inserted sub-band images HL_(n),LH_(n) and HH_(n) at step S15.

In the present embodiment, a 2-level DWT is performed. However, thepresent invention is not limited thereby. That is, if an n-level DWT maybe performed, a HVS model may be obtained from the sub-band imagesLL_(n) at step S11 and the fingerprint basic block is repeatedlyinserted into the sub-images HL_(n), LH_(n) and HH_(n).

In the present embodiment, the size of original image is 512×512, andthe size of fingerprint basic block is 32×32. The fingerprint basicblock is inserted to each sub-band image HL₂, LH₂ or HH₂ more than 16times. The reason of repeatedly inserting is for using the fingerprintinserted image as a template to correct a transformed image by rotatingor scaling among the geometrical attacks. If the fingerprint block isinserted repeatedly in a unit of block size, a constant auto-correlationcan be obtained when the fingerprint is extracted from the image. It iscalled as a self reference pattern. It is used as the template tocalculate inverse information about geometric transformation and theimage is corrected according to the calculated inverse information.

FIG. 3 shows a generation of a multi-bit fingerprint signal in the stepS12 in the method of inserting the multi-bit fingerprint shown in FIG.1.

In FIG. 3, a step for generating N fingerprint group FP 1 to FPN as longas a length of a message from 62 random signals each of which having a1024-bit length per each message. Each message is one of 62 signalsrepresenting 52 uppercase and lowercase alphabets and 10 numbers. Such62 alphabets and numbers are expressed as a 1024-bit random signal by asecurity key. In the present embodiment, a 64-bit of fingerprint isinserted in order to insert a message of eight ciphers.

FIG. 4 shows a generation of a fingerprint block in the method ofinserting a multi-bit fingerprint according to an embodiment of thepresent invention. That is, FIG. 4 shows transforming of the multi-bitfingerprint signal, that is, the message of eight ciphers, to a 32×32basic block configured of −1 s and +1 s.

In FIG. 4, each message of 8 figures is a 1024 bit random signalconfigured of −1 s and +1 s, which is generated by a security key. A1024-bit merge fingerprint signal configured of number in a range of −9to +9 is generated by merging the 1024-bit random signal with a syncpattern that is another random signal. In order to insert the generatedmerge fingerprint signal into the image, the merge fingerprint signal istransformed to a new signal configured of −1 and +1. For example,numbers in the merge fingerprint signal, which are smaller than 0, istransformed to −1, and numbers in the merge fingerprint signal, whichare larger than 0, is transformed to +1. Then, the one-dimensional 1024merge fingerprint signal is rearranged to a two-dimensional 32×32fingerprint block.

FIG. 5 shows an insertion of a fingerprint block into wavelet sub-bandareas of the original image according to an embodiment of the presentinvention. As shown, the 32×32 fingerprint block generated in FIG. 4 isrepeatedly inserted in to each of the sub-band images HL₂, LH₂ and HH₂after performing a two-level DWT on the original image as shown in FIG.5.

Hereinafter, a method of extracting a multi-bit fingerprint according tothe present invention will be described with reference to FIGS. 2 and 6to 8.

FIG. 2 schematically shows a method of extracting a multi-bitfingerprint according to an embodiment of the present invention. Asshown in FIG. 2, the method of extracting a multi-bit fingerprintincludes: estimating original signal having a fingerprint from afingerprint inserted image at step S21; obtaining a peak from aself-reference pattern obtained by an auto-correlation of the estimatedoriginal signal at step S22; extracting rotation and scaling informationfrom the detected peak and correcting the original signal having thefingerprint based on the extracted rotation and scaling information atstep S23; obtaining an estimated fingerprint signal from the correctedoriginal signal, extracting translation information from a crosscorrelation peak between the estimated fingerprint signal and the syncpattern signal, and correcting the translation of the original signalhaving the fingerprint at step S24; and extracting a fingerprint fromthe rotation, scaling and translation corrected original signal at stepS25.

In the step S21 for estimating the original signal having thefingerprint, a noise component having a fingerprint is extracted from afingerprint inserted image. Generally, a wiener filter or a high-passfilter is used. In the present embodiment, the wiener filter is used.

In the step S22 for detecting the peak, the auto-correlation of theestimated original signal having the fingerprint. As a result, the peakrepeatedly shown in the self-reference pattern generated by theauto-correlation is detected.

In the step S23, the rotation and scaling information is extracted fromthe peak information detected at the step S22. In the present invention,information about a straight line formed of the extracted peaks isextracted and the rotation and scaling information is extracted frominformation about a slope of the straight line and distances betweenpoints forming the straight line.

FIG. 6 shows a generation of a synch part signal used for correcting atranslation of an original image according to the present invention.

While inserting the fingerprint as described with reference to FIG. 4,the 1024-bit synch pattern signal generated by the security key isrearranged in a two dimensional formation and accordingly, a twodimensional 32×32 fingerprint block is generated. The synch patternsignal is repeatedly inserted to sub-band images HL_(n), LH_(n) andHH_(n) obtained by performing the DWT on an image having all pixels ofzero. Then, the synch pat signal is generated by performing the inverseDWT on these sub-band images.

Referring to FIG. 6, the fingerprint block inserted image is decomposedinto 128×128 blocks, and the divided 128×128 blocks are merged togenerate the sync part signal. The sync part signal is used to correctthe translation of the image when extracting the fingerprint. In thepresent embodiment, the size of the image having all pixels of 0 is asize of 512×512 which is identical to the size of the original image.

FIG. 7 shows a generation of an estimated fingerprint part signal usedto correct the translation of the image according to an embodiment ofthe present invention. In particular, FIG. 7 shows the generation of theestimated fingerprinting part signal for correcting the translationusing the rotating and scaling corrected image.

At first, an original signal is estimated from the rotating and scalingcorrected image. The original signal can be easily obtained from adifference between the rotating and scaling corrected image and an imagefiltered by the wiener filter. The estimated fingerprinting part signalis generated by adding the estimated original signal with the 128×128divided images. The estimated fingerprinting part signal is used tocorrect the translation transformation with the synch part signal whileextracting the fingerprint.

FIG. 8 shows a correction of translation transformation and anextraction of the fingerprint information in a method of extracting amulti-bit fingerprint according to an embodiment of the presentinvention.

In order to correct the translation formation of image, the crosscorrelation is obtained between the synch part signal and the estimatedfingerprinting part signal. From the obtained cross correlation, alocation of cross correlation peak between the synch part signal and theestimated fingerprinting part signal is obtained. The level oftranslation formation is detected based on the obtained location of thecross correlation peak. A circular shift is performed using the locationpeak as an origin (0.0) to merge sub-band images. As a result, asub-band merging signal M₁₃ part is generated. Then, the fingerprint,64-bit of eight text messages, is extracted from the original image byobtaining a cross correlation between the sub-band merging signal M_partand random sequences of fingerprint group (FP) shown in FIG. 3.

Although the preferred embodiments of the present invention have beendisclosed for illustrative purpose, those skilled in the art willappreciate that various modifications, additions and substitutions canbe made without departing from the scope and spirit of the invention asdefined in the accompanying claims.

1. A method of inserting a multi-bit fingerprint based on a waveletcomprising the steps of: a) decomposing an original image into a firstsub-band image having low frequency band columns and rows, a secondsub-band image having high frequency band columns and low frequency bandrows, a third sub-band image having low frequency band columns and highfrequency band rows and a fourth sub-band image having high frequencyband columns and rows by performing an n-level discrete wavelettransformation on an original image; b) obtaining a human visual systemmodel from the first sub-band image; c) generating an N×N fingerprintbasic block by performing a message modulation on a multi-bitfingerprint signal with a security key and adding a synch pattern to themodulated signal; d) repeatedly inserting the fingerprint basic block into the second, the third and the fourth sub-band images with referenceto the human visual system model; and e) generating a fingerprintinserted image by performing an inverse discrete wavelet transformationon the first sub-band image and the fingerprint basic block insertedsecond, third and fourth sub-band images.
 2. The method of claim 1,wherein in the step C), the multi-bit fingerprint signal is modulatedwith the security key by selecting a message having predeterminedalphabets and numbers and transforming the selected message with thesecurity to a random signal.
 3. The method of claim 2, wherein thefingerprint basic block in the step c) is generated to have apredetermined size by obtaining a merged fingerprint signal throughadding a synch pattern to the generated random signal and rearrangingthe merged fingerprint signal in two dimensional formation.
 4. A methodof extracting a multi-bit fingerprint based on a wavelet comprising thesteps of: a) estimating original signal having a fingerprint from afingerprint inserted image; b) detecting a peak from a self-referencepattern obtained from an auto-correlation of the estimated originalsignal; c) extracting rotation and scaling information from the detectedpeak and correcting a rotation transformation and a scalingtransformation of the original signal having the fingerprint based onthe extracted rotation and scaling information; d) obtaining anestimated fingerprint part signal from the corrected original signal,extracting translation information from a cross correlation peak betweenthe estimated fingerprint part signal and a synchronization signal, andcorrecting a translation transformation of the original signal havingthe fingerprint; and e) extracting a fingerprint from the rotation,scaling and translation corrected original signal using a sub-band mergesignal.
 5. The method of claim 4, wherein in the step c), informationabout a straight line formed of the extracted peaks at the step b) isobtained and the rotation and scaling information is extracted based ona slope of the straight line and a distance between points forming thestraight line.
 6. The method of claim 4, wherein the synchronizationsignal in the step d) is a signal inserted into a fingerprint basicblock while inserting a fingerprint and is generated by dividing afingerprint block inserted image into divided images each having apredetermined size and merging the divided images.
 7. The method ofclaim 4, wherein the estimated finger print part signal of the step d)is generated by dividing the estimated original signal into dividedimages having a predetermined size based on a center point and addingthe divided images.
 8. The method of claim 4, wherein in the step c),the sub-band merge signal is obtained by merging sub-band imagesobtained through performing a discrete wavelet transformation on arotation, scaling, and the fingerprint is extracted from the image by across correlation between the sub-band merge signal and a random signalof a fingerprint group.